The main purpose of this paper is to expand the usage of OCR (Optical character recognition) as this is only implemented over images and to extend this Video OCR is introduced in a way to help to retrieve the information from the video without playing the video. Video OCR is executed with the assistance of OpenCv2 module and PyTesseract [7] at the side of SWT approach which all pretty collectively make an ideal aggregate to offer an appropriate content from the video (i.e., Lecture video or any kind of video which has slides or text on the background of the video) [2,4].This technique is performed in a well-designed along with easy steps to provide us an correct end result of the facts from the video into textual files. In addition to this we also added Speech Recognition module within the project to support the video along with the text file. This speech delivered by the faculty (i.e., instructor/educator/teacher), or an educator will be also resulted in a text file.